Included in this archive are all data and code needed to replicate the tables and figures in:

Asquer, Raffaele, Miriam A. Golden, and Brian T. Hamel. �Corruption, Party Leaders, and Candidate Selection: Evidence from Italy.� Legislative Studies Quarterly.

Contact Brian Hamel at hamel.t.brian@gmail.com with questions. Data:- �ansa.dta� gives data on the number of front-page news stories about corruption in ANSA�s daily news summary from 1991 to 1995. The data are at the month-year level.-  �repubb.dta� gives data on the number of front-page news stories about corruption in La Repubblica from 2006 to 2013. The data are at the month-year level.
- �dta.RData�, �leg_x_xi.RData�, and �leg_xv_xvi.RData� are our main datasets. �leg_x_xi.RData� and �leg_xv_xvi.RData� are subsets of �dta.RData.� Each are legislator-legislature level datasets, and include in them our corruption-related press mentions variable as well as all covariates included in our models.
Code: 
- �descriptives.R� replicates Figure 1, Figure 2, and Figure 3, and Table A1. Figures 1 and 2 give the monthly number of front-page news stories about corruption from 1991-1995 (Figure 1) and 2006-2013 (Figure 2). Figure 3 plots the distribution of our corruption-related press mentions variable for all legislators (Figure 3A) and corrupt legislators (Figure 3B) by legislature. Table A1 gives the minimum, mean, and maximum for each variable included in our main estimates by legislature.- �main.R� replicates Table 1, Figure 4, and Table A2. Table 1 gives our main logit estimates of the effect of corruption-related press mentions on renomination (conditional on the legislative period). Figure 4 gives the predicted probabilities of renomination associated with these models. Table A2 shows how the effects also vary by majority party status. 